Media Server 25.1
Media Server Help

# Improve Accuracy by Optimizing the Recognition Network

Face recognition uses a neural network to determine how closely a face in the ingested media matches the faces in your training database. The default neural network that is supplied with Media Server can be used with any face database.

To improve recognition accuracy, Media Server can fine-tune this neural network for the data in a single face database. To use the fine-tuned network, a face recognition task must use only that database, and the database must meet several requirements:

- The database must have been created with fine-tuning enabled (use the `finetuning` parameter in the action `CreateFaceDatabase`).
- The database must contain a reasonable number of faces. OpenText recommends more than 50.
- The database must contain multiple training images for most or all of the faces.

NOTE: OpenText recommends that you fine-tune the neural network only if your training data is similar to the media that you will ingest. For example, if you are planning to ingest video captured from a CCTV camera, the training data should ideally have been captured from CCTV. In some cases, using `action=FinetuneFaceDatabase` can result in overfitting and reduce recognition accuracy. If you find that accuracy is reduced, you can revert to the default neural network by setting `DisableFineTuning=TRUE` in your face recognition task.

To optimize the neural network, run the action `FinetuneFaceDatabase`. Run this action as the final step, after all other training is complete. OpenText recommends running the action `BuildAllFaces` first, to ensure that all of the images have been trained. For example:

    /action=BuildAllFaces&Database=politicians
    /action=FinetuneFaceDatabase&Database=politicians

The optimized network is used automatically, as long as you set the `Database` parameter in your face recognition task. For more information about configuring a face recognition task, see Recognize Faces.

After optimizing the network, you can add faces to the database, or remove them, as normal. However, OpenText recommends that you run `FinetuneFaceDatabase` again whenever you make significant changes to the training.

Copyright 2024 Open Text
Version 25.1 | Last updated January 2025

Send documentation feedback

Close

Send documentation feedback

To send feedback using your default email client, open an email window.

Otherwise, send your feedback and the information below to MFI-swpdl.idoldocsfeedback@opentext.com.

We appreciate your feedback!

Product: Knowledge Discovery Media Server 25.1

Topic Title: Improve Accuracy by Optimizing the Recognition Network